Principal Program Manager

Who you are

• You have demonstrated hands-on experience building and deploying applied AI solutions, including AI agents and use-case-specific model fine-tuning
• You have practical experience with enterprise AI ecosystems (e.g. Google Cloud, Gemini) and hands-on usage of tools such as GPT or Claude, including API and workflow integrations
• You have strong programme delivery capabilities, translating business needs into prioritised execution plans and driving transformation initiatives end to end
• You can manage senior stakeholders effectively, aligning technical implementation with business objectives
• You have experience operating within scaled organisations where AI solutions are already live and integrated into core processes
• You have 8–12 years of combined technical and business working experience. A broader machine learning background, Python and SQL proficiency, and vendor management experience are considered an advantage
• Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!

What the job involves

• We’re looking for a hands-on Principal Program Manager (AI Project Charter) to drive impact within Rides Central Operations
• You’ll solve complex operational problems by designing scalable AI solutions that deliver measurable results across markets
• You’ll personally design and implement AI tools, agents, dashboards, and decision systems, working cross-functionally while maintaining strong individual ownership. You’ll also help define how AI initiatives are prioritised and governed across Rides
• This is an individual contributor (IC) role with high ownership and no direct reports. It’s built for someone eager to build, own, and deliver real change
• Build and deploy AI tools, agents, dashboards, and decision systems for Rides Operations, covering areas such as diagnostics, optimisation, forecasting, policy enforcement, and reporting automation, moving from prototype to production-ready solutions
• Translate operational complexity into scalable AI solutions with measurable impact, identifying high-friction problems across markets and defining use cases that improve cost, efficiency, reliability, and growth
• Deliver independently, minimising dependencies while partnering where scale or integration is required, using internal data, APIs, large language models (LLMs), and automation frameworks to ship usable tools even with limited Engineering, Data, or Product bandwidth
• Create clear decision materials for leadership, highlighting trade-offs, risks, and impact, running structured AI reviews, and aligning priorities with operational and financial outcomes
• Develop scaling playbooks and drive adoption across regions, guiding pilots through rollout to steady state, tracking performance, and iterating based on usage and feedback
• Establish principles and governance for responsible AI use in Operations, defining guardrails to ensure solutions are explainable, locally compliant, and aligned with long-term platform standards